Operations research and business analytics are disciplines related to applying data-driven analytical and mathematical methods to assist in making better decisions. Business analytics focuses on developing new insights and knowledge from data, and transforming this knowledge into better business decisions. It is based on a broad set of well-known methodologies such as statistics, management science, operations research and artificial intelligence. Successful applications of operations research and business analytics are abundant in industries such as transportation, logistics, healthcare, manufacturing and service companies, along with public and private organizations, etc. Business analytics and operations research extract high-value business insights from the immense amount of available data, and in today’s highly complex business environment these tools can provide an outstanding competitive advantage.
Helena holds a B.A., a master’s degree in Statistics and Operations Research from the University of Lisbon, Portugal, and a Ph.D. in Operations Research from Cornell University, New York, USA. She has been involved in different research projects and consulting for firms in the area of operations research, transportation and logistics. Helena has published several articles in prestigious international scientific journals and has presented her work at international congresses and conferences. Helena teaches in various undergraduate, master’s and PhD programs in several European universities. She is currently the director of the Business Analytics Research Group and a researcher at the Center for Operational Research at the University of Lisbon. Her research interests include operations research, business analytics, scheduling, combinatorial optimization, metaheuristics, iterated local search, heuristic search optimization, vehicle routing, job-shop scheduling, supply chain management, logistics, production and operations management.
Operations research, logistics, metaheuristics, iterated local search, combinatorial optimization, scheduling, supply chain management
Main Research Project
2014-2016 – Business Analytics Models for Horizontal Cooperation in Transportation and Logistics. Research Project: TRA2013-48180-C3-2-P, Ministerio de Economía y Competitividad, Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia, Spain. Research Director (IP: Helena Ramalhinho Lourenço).
See complete list: Publications and CV
Grasas A. And Ramalhinho-Lourenço H. (2015), Teaching Distribution Planning: A problem-based learning approach. International Journal of Logistics Management (accepted for publication).
Grasas A., Juan, A.A. and Lourenço H.R. (2014), SimILS: A Simulation-based extension of the Iterated Local Search metaheuristic for Stochastic Combinatorial Optimization, Journal of Simulation (advance online publication 3 October 2014) doi:10.1057/jos.2014.25.
Grasas A., Ramalhinho H., Pessoa L.S., Resende M.G.C., Caballé I. and Barba N. (2014), On the Improvement of Blood Sample Collection at Clinical Laboratories, BMC Health Services Research 14:12. DOI:10.1186/1472-6963-14-12.
Martins P., Ladrón A. and Ramalhinho H. (2014), Maximum Cut-Clique Problem: ILS Heuristics and a Data Analysis Application, International Transactions in Operational Research (accepted for publication July 25, 2014; published online September 5, 2014). doi: 10.1111/itor.12120.
Lourenço H.R., Martin O. and Stützle T. (2010), Iterated Local Search: Framework and Applications. In Handbook of Metaheuristics, 2nd. Edition. Vol.146. M. Gendreau and J.Y. Potvin (eds.), Kluwer Academic Publishers, International Series in Operations Research & Management Science, pp. 363-397.
Juan, A. A., Faulin, J., Ferrer, A., Lourenco H.R., and Barros, B. (2013), MIRHA: Multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problem. TOP: Volume 21, Issue 1, Pages 109-132. doi10.1007/s11750-011-0245-1.
Giménez C. and Lourenço H.R. (2008), e-SCM: Internet’s impact on Supply Chain Processes. International Journal of Logistics Management 19(3): 309-343.
Lourenço H.R., Paixão J.P. and Portugal R. (2009), Driver Scheduling Problem Modelling. Public Transport: Planning and Operations. 1(2):103-120, doi: 10.1007/s12469-008-0007-0.
Journal of Metaheuristics: Methods and Applications, Editorial Advisory Board.
Journal of Applied Operational Research (JAOR),Editorial Board
Journal of Industrial Engineering and Management, Editorial Board (Production, Logistics, Quality, and Operational Research)